Predicting multi-vascular diseases in patients with coronary artery disease

Background: Because of its systemic nature, the occurrence of atherosclerosis in the coronary arteries can also indicate a risk for other vascular diseases. However, screening program targeted for all patients with coronary artery disease (CAD) is highly ineffective and no studies have assessed the risk factors for developing multi-vascular diseases in general. This study constructed a predictive model and scoring system to enable targeted screening for multi-vascular diseases in CAD patients. Methods: This cross-sectional study includes patients with CAD, as diagnosed during coronary angiography or percutaneous coronary intervention from March 2021 to December 2021. Coronary artery stenosis (CAS) and abdominal aortic aneurysm (AAA) were diagnosed using Doppler ultrasound while peripheral artery disease (PAD) was diagnosed based on ABI score. Multivariate logistic regression was conducted to construct the predictive model and risk scores. Validation was conducted using ROC analysis and Hosmer-Lemeshow test. Results: Multivariate analysis showed that ages of >60 years (OR [95% CI] = 1.579 [1.153-2.164]), diabetes mellitus (OR = 1.412 [1.036-1.924]), cerebrovascular disease (OR = 3.656 [2.326-5.747]), and CAD3VD (OR = 1.960 [1.250-3.073]) increased the odds for multi-vascular disease. The model demonstrated good predictive capability (AUC = 0.659) and was well-calibrated (Hosmer-Lemeshow p = 0.379). Targeted screening for high-risk patients reduced the number needed to screen (NNS) from 6 in the general population to 3 and has a high specificity of 96.5% Conclusions: Targeted screening using clinical risk scores was able to decrease NNS with good predictive capability and high specificity


Introduction
Atherosclerosis underlines some of the major cardiovascular diseases which are the leading cause of mortality worldwide.Due to its systemic nature, atherosclerosis in the coronary arteries may indicate occurrences in other arteries. 1Coronary arterial disease (CAD) is associated with peripheral artery disease (PAD), carotid artery stenosis (CAS), and abdominal aortic aneurysm (AAA).3][4] Therefore, the screening in patients with CAD is justifiable in assessing the risk of atherosclerosis occurrences in other arteries.
CAD is one of the leading causes of mortality worldwide with a substantial incidence rate.According to the Centers for Disease Control and Prevention (CDC) in the United States, a total of 20.1 million adults aged 20 years old and older have CAD. 5 Screening for PAD, carotid artery stenosis, and AAA enable early detection, risk stratification, and early cardiovascular treatment; all in favor of reducing morbidity and mortality. 6,7However, screening program targeting all CAD patients is highly ineffective, costly, and requires multiple resources such as specific instruments and trained technicians.On the other hand, screening for early detection of some vascular diseases, e.g., PAD, in patients with significant CAD was not shown to be more beneficial compared to a routine medical checkup. 8Therefore, targeted screening in patients with CAD requires careful consideration based on risk factors for atherosclerosis in other arteries.
Targeted screening contributes to early detection while being more time and cost-effective than general screening; it can be beneficial for diseases previously deemed not necessary to screen.A study specifically assessed targeted screening for AAA was already done involving a small subset of indigenous people in Borneo. 9No research has been conducted to assess the predictors for developing multi-vascular diseases, including PAD, CAS, and AAA in patients with CAD.Furthermore, no studies assessed the number needed to screen (NNS) of screening for multi-vascular diseases in CAD patients and the impact of the clinical risk scoring system for said NNS.We hypothesize that a risk-scoring tool to measure the risk of other vascular diseases in CAD patients is feasible to construct and can be applied for targeted screening; in return, the risk-scoring tool can reduce the NNS for asymptomatic multi-vascular diseases.Therefore, this study aims to investigate factors predicting the occurrence of multi-vascular diseases in patients with CAD while constructing a predictive model and scoring system to enable targeted screening for future uses.

Methods
This study was conducted based on the STROBE guideline for observational studies. 10The study protocol was approved by the National Cardiovascular Center Harapan Kita Hospital committee of ethics (ethics approval number: LB.02.01/VII/509/KEP005/2021).All patients gave written informed consent prior to the recruitment of the study and were free to decline participation.

Patient selection
This cross-sectional study was conducted at the National Cardiovascular Center of Harapan Kita Hospital from March 2021 to December 2021.All patients who underwent elective coronary angiography or percutaneous coronary intervention from March 2021 to December 2021 were initially included.Patients diagnosed with coronary artery disease (CAD) were eligible for inclusion in our study.We excluded patients with previously diagnosed CAD that were hospitalized for other reason than elective coronary angiography or coronary angioplasty.We also excluded patients with connective tissue disorder.All included patients were concomitantly screened for vascular disease.The primary outcome of interest was vascular diseases in other vascular territories.For all patients, we examined the list of variables relating to sociodemographic characteristics, cardiovascular risk factors, and other related diseases.
The diagnosis of hypertension was based on documented medical history, the use of antihypertensive drugs, and the presence of elevated systolic and/or diastolic blood pressure according to European Society of Cardiology guidelines. 11iabetes mellitus was diagnosed based on documented medical history through the use of hypoglycemic agents, and/or laboratory criteria according to the American Diabetes Association (ADA) 2021.12 Dyslipidemia was defined based on documented medical history and the use of lowering lipid agents or laboratory criteria according to the National REVISED Amendments from Version 1 I have made revisions as per the suggestions of the reviewers, mainly to shorten the literature in Discussion.The prevalence of metabolic syndrome in our study was revised after reviewing the existing data.However, these revisions do not change the results of this study.
Cholesterol Education Program's Adult Treatment Panel III (NCEP-ATP III). 13Metabolic Syndrome was also defined according to the NCEP-ATP III.Information on the history of cerebrovascular disease (transient ischemic attack or stroke) was collected from the patient's reports or medical records. 13CAD was diagnosed using angiography.The presence of coronary lesions was determined using visual estimation.Coronary artery lesions were considered as CAD if 1) at least one major epicardial artery or its major branches have significant stenosis (70% for left anterior descending artery, left circumflex artery, right coronary artery, or 50% for left main trunk) or 2) the patient was previously hospitalied for treatment of coronary artery lesions (balloon, stent, or coronary artery bypass grafting).
Lower extremity peripheral arterial disease (PAD) was defined with 1) ankle-brachial index of < 0.9 or 2) the patient was previously treated for PAD. 14Evaluation of carotid artery stenosis (CAS) and AAA was conducted using bedside ultrasound Affiniti 70 (Philips, Amsterdam, Netherlands) by a cardiovascular technician blinded to other data.Peak systolic velocity, end-diastolic velocity, and intima-media thickness of the common carotid artery and internal carotid artery were calculated to evaluate CAS.The degree of CAS was classified according to Grant et al. 15 CAS was considered significant if 1) the presence of stenosis ≥50% from ultrasound examination or 2) the patient was previously treated for CAS (carotid stenting or carotid endarterectomy).AAA was defined as an enlargement of the abdominal aorta with a diameter of ≥3 cm or a previously treated AAA lesion (Endovascular aortic repair/EVAR or open surgical repair). 16he maximum and minimum abdominal aortic diameter (anteroposterior or transverse axis) were obtained.
Potential bias for each diagnosis of vascular disease were minimized by involving third-party examiners who were not aware of the existence of this study.

Statistical analysis
Categorical variables were expressed in the form of numbers and percentages, whereas continuous variables were expressed as their mean valueAESD in data with normal distribution or their median (interquartile range) value in data without normal distribution.We compared categorical variables using Pearson's chi-square or Fisher's exact test while continuous variables were compared using the Student t-test or Mann-Whitney U test.We conducted multivariable stepwise logistic regression to generate prediction models with the primary endpoint of multivascular disease incorporating clinical variables.All variables with p value of <0.25 by univariate analysis were included in the multivariable model.The selection of variables for retention was based on p value of <0.05.We additionally performed the Hosmer-Lemeshow test to assess the goodness of fit of the model and plot the observed versus predicted data graph.
For each significant variable from multivariate analysis, a regression β coefficient was obtained, and a scoring system was created to predict the incidence of coexisting vascular diseases.Points for the scoring prediction rule were assigned by weighing each significant variable compared to the total β coefficient.Then, points were made using the weighted coefficients with rounding to the nearest whole number.We created the cutoff points to classify patients with low, moderate, and high-risk probability, respectively.To test the model discrimination, C-statistic was also conducted to calculate the area under the curve.We also conducted internal validation by bootstrap using the same amount of included samples.All statistical analyses were performed using SPSS version 23 (IBM, New York, USA) and STATA version 16 MP (StataCorp, Texas, USA).

Results
A total of 1314 patients with CAD were identified; 203 (15.4%) patients have multi-vascular disease.All patients had complete medical record data and, therefore, no missing data in this study.Sociodemographic and clinical data are shown in Table 1.Amongst the variables in patient's demographics, there was a significant difference in the proportion of patients with cerebrovascular disease, CAD three-vessel disease (CAD3VD), and CAD left main disease (CAD-LM).The prevalence of PAD, CAS, and AAA in patients with CAD were 143 (10.9%), 59 (4.5%), and 19 (1.4%), respectively.The overlap between vascular diseases is shown in Figure 1.There is a difference in prevalence of vascular diseases in CAD patients with one, two, and three-vessel disease (Table 2).
Univariate analysis demonstrated individuals with older age, diabetes mellitus, cerebrovascular disease, CAD3VD, and left main disease were more likely to have multivascular disease (Table 3).After a multivariate analysis, four variables were retained to form the final clinical model: ages of ≥60 years (OR: 1.579; 95% CI: 1.153-2.164),diabetes mellitus    3).
The area under the curve of the model was 0.659 (95% CI: 0.617-0.700)and was well calibrated (Hosmer-Lemeshow test p=0.379;).Using bootstrap validation, the optimism-corrected area under the curve was 0.653 (95% CI: 0.610-0.695),which represents the predictive ability of the model (Figure 2).Those four variables were assigned weighted points scores for the final clinical prediction of multi-vascular disease based on the magnitude of the β coefficient (Table 4).We designated a score of 0-2 as low probability (9% of chance), 3-5 as moderate probability (21%), and 6-8 as high probability (42%).The discriminatory ability of the scoring system was moderate (AUC: 0.649; 95% CI: 0.610-0.687).
Based on our data, targeted screening for patients with moderate risk or higher decreases the number needed to screen (NNS) from six to five while targeted screening for patients with high risk reduces the NNS from six to three.Targeted screening for patients with moderate risk or higher had the most balanced results of diagnostic values with positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity of 45,1%, 86,2%, 15,8%, and 96,5% respectively.

Discussion
This is the first study in Indonesia, to investigate factors predicting the occurrence of multi-vascular diseases in patients with CAD.Our findings show that three vascular diseases were all encountered in CAD patients namely; PAD with prevalence of 10.9%, CAS with prevalence of 4.5% and lastly AAA with prevalence of 1.4%.2014) demonstrated that 2.5% to 14.4% of all CAD also had asymptomatic AAA, hence confirming the presence of AAA in CAD. 4 The lower prevalence of the aforementioned predictors in this findings might be due to the younger patients recruited in our study, compared to others.8][19] The shift of peak prevalence towards younger subjects in Indonesia might be caused by the higher frequency of CAD risk factors encountered in younger generation.This is supported by the study of Hussain et al.
(2016), which demonstrated a higher population attributable risk proportion (PAR) percentages of smoking habits, hypertension, excess body weight, diabetes mellitus and hypercholesterolemia in CAD subjects less than 55 years old compared to older population. 20 The association between the severity of CAD and the extent of atherosclerosis was also observed in other vasculatures.The extent of fat deposit along coronary vasculatures is proportional to the severity of atherosclerosis, as demonstrated by the increased expression of interleukin-6 (IL-6) and leptin and the decreased expression of serum adiponectin. 21Our data showed no significant increased AAA prevalence in relation with CAD severities.This might be due to a small prevalence of AAA, in which affected to no statistical significance.
Given the final model in our study, Honda T, et al in the Hisayama study (2022) conducted a prospective observational study and constructed a risk prediction model for the development of ASCVD in Japanese adults.They found that age, sex, systolic blood pressure, diabetes mellitus, proteinuria, smoking habit and regular exercise are all predictors of ASCVD occurrence. 22The Hisayama study, in contrast to ours, used Japanese people who had no prior history of CVD.Consequently, they conducted a prospective observational study and followed the subjects for 24 years.
In order to construct risk prediction model, risk scoring was made from β-coefficient obtained from the multivariate analysis.The calibration of the final model fulfilled the goodness of fit, utilizing the Hosmer-Lemeshow test.Determinant capability of risk scoring was shown to be moderately good with AUC of 65.9%.Likewise, this determinant was quite comparable with another risk prediction model in those with stable CAD, carried out by Badheka et al (2011).They established the predictors such as: history of hypertension, smoking, age and history of diabetes with AUC of 68.6%. 23dditionally, our study demonstrated that general screening of all CAD patients resulted in 15.4% cases with multivascular disease, and number needed to screen (NNS) was 6.Meanwhile, targeted screening for patients with high-risk based on our own risk scoring would reduce the NNS from 6 to 3 identifying 45% CAD patients suffered other vascular disease.Consequently, our clinical risk scoring proved to have a very high specificity of 96.5%.Although choosing an NNS of 6 is arbitrary, but the decrement of NNS value from 6 to 3 was quite impressive.

Study limitation
The limitation of this study is the cross-sectional design, which does not measure the potential for future vascular disease incidents and enabled bias.Potential bias in this study primarily stems from assessor's confirmatory bias, when diagnosing the incident of asymptomatic vascular disease.However, this confirmatory bias was lessened by involving third party examinators.Temporal and external validation is actually needed to confirm the study results.

Conclusion
Patients with CAD who have diabetes mellitus, cerebrovascular disease, CAD3VD, and above 60 years old are associated with increased odds of multi-vascular disease.By using risk scoring tool made from these risk factors, targeted screening in high-risk patients decrease the number needed to screen in half with high specificity. patients.
The study methodology involves a cross-sectional design and the use of various diagnostic techniques.The inclusion and exclusion criteria are clearly defined, and the diagnostic techniques for various vascular diseases are explained.The article describes the statistical methods used, including univariate analysis, multivariable stepwise logistic regression, Hosmer-Lemeshow test, and the creation of a scoring system.The article also states that potential bias for each diagnosis of vascular disease was minimized by involving third-party examiners who were not aware of the existence of the study.
The results demonstrate the effectiveness of the predictive model in reducing the number needed to screen (NNS) and achieving high specificity.The area under the curve (AUC) of the model is reported as 0.659, indicating good predictive ability.However, it would be useful to provide the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the model at a chosen cutoff point.This information would further illustrate the diagnostic performance of the model.Overall, the discussion effectively acknowledges and discusses the study limitations.The discussion briefly mentions the need for external validation to confirm the generalizability of the risk scoring tool.

If applicable, is the statistical analysis and its interpretation appropriate? Yes
Are all the source data underlying the results available to ensure full reproducibility?Yes

Are the conclusions drawn adequately supported by the results? Yes
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Cardiology and vascular medicine I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.
Thank you for the suggestion.The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the model at a chosen cutoff point were demonstrated in Table 5. Performance of risk score in detecting vascular disease in CAD patients.Because the cutoff point of our scoring system was two (three groups), we compared the at least moderate risk vs. low risk, and at least high risk vs. low risk.

Marc Vuylsteke
Saint Andries Hospital, Tielt, Flanders, Belgium This paper contains an interesting cross-sectional study regarding the risk factors of developping multi-vascular diseases in patients with coronary artery disease.However I do have some comments: Major comments Methods: Exclusion criteria: "We excluded patients with previously diagnosed CAD".But further you state: "Coronary artery lesions were considered as CAD if 2) the patient was previously hospitalized for treatment of coronary artery lesions".Isn't that a contradiction? 1.
Risk factors: 'hypertension': how do you quantify hypertension.Some patients have only very mild hypertension, some severe hypertension.Similar regarding PAD, diabetes.Is it possible to distinguish the severity of these conditions? 2.
Risk-factors: ankle-brachial-index of >0.9: this is a very mild level of PAD.Most of those patients are asymptomatic and many of them will stay asymptomatic.Why not looking for the more severe form of PAD (ABI<0.4)?How do you assess ABI in patients with diabetes?As you know, this examination is not well reliable in diabetics given the presence of media sclerosis.

3.
For assessing the risk of developing AAA, shouldn't we look for a positive family history of AAA? 4.
Table 1: Patient's baseline characteristics: Metabolic syndrome was found in 51.1 % of included patients, however only 14.7% were obese?How can you explain this?

5.
Please shorten the discussion significantly.The literature overview is much too long.6.

3.
Results: "A total of 1314 patients with CAD were identified; 203 patients have [multi vascular disease]".

If applicable, is the statistical analysis and its interpretation appropriate? Yes
Are all the source data underlying the results available to ensure full reproducibility?Yes

Are the conclusions drawn adequately supported by the results? Yes
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Vascular surgery I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.patient was previously hospitalized for treatment of coronary artery lesions".Isn't that a contradiction?We have revised this the sentence in the first paragraph of patient selection: We excluded patients with previously diagnosed CAD that were treated by medical therapy and revascularization therapy into We excluded patients with previously diagnosed CAD that were hospitalized for other reason than elective coronary angiography or coronary angioplasty.
2. Risk factors: 'hypertension': how do you quantify hypertension?Some patients have only very mild hypertension, some severe hypertension.Similar regarding PAD, diabetes.Is it possible to distinguish the severity of these conditions?In this study, we did not quantify the severity of hypertension, PAD and diabetes.We just simply categorized the patients whether they have hypertension, PAD or diabetes according to ESC guidelines, the value of ankle brachial index and ADA guidelines respectively.
3. Risk-factors: ankle-brachial-index of >0.9: this is a very mild level of PAD.Most of those patients are asymptomatic and many of them will stay asymptomatic.Why not looking for the more severe form of PAD (ABI<0.4)?How do you assess ABI in patients with diabetes?As you know, this examination is not well reliable in diabetics given the presence of media sclerosis.The purpose of this study is to screen the presence of multi-vascular disease in patients with proven coronary disease and subsequently propose a risk score that enable targeted screening.Thus, the screening would be for those who are considered high risk but asymptomatic.Patients with ABI of <0.4 usually suffer from more severe PAD and would have already come for treatment.ABI is not a perfect diagnostic tool in the presence of media sclerosis; however it is still recommended for screening purposes by several professional organization through their guidelines (ESC, ACC/AHA, SVS, NICE) even in the presence of diabetes and chronic kidney disease.

4.
For assessing the risk of developing AAA, shouldn't we look for a positive family history of AAA? Very good point, unfortunately AAA is still underdiagnosed in our population.Thus the presence of family history might not be accurately identified.

Table 1:
Patient's baseline characteristics: Metabolic syndrome was found in 51.1 % of included patients, however only 14.7% were obese?How can you explain this?The criteria of metabolic syndrome was based on NCEP-ATP III Definition, in which 3 out of five criteria including waist circumference, blood pressure, LDL level, HDL Level and fasting glucose level.We re-analyzed metabolic syndrome using the definition, resulting in a prevalence of 37.7%.The difference between the 37.7% prevalence of metabolic syndrome and the 14.7% prevalence of obesity can be attributed to the presence of other criteria used to diagnose metabolic syndrome.
Interests: No competing interests to disclose.Reviewer Report 10 July 2023 https://doi.org/10.5256/f1000research.147721.r182362© 2023 Vuylsteke M. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

6 .
Please shorten the discussion significantly.The literature overview is much too long.We have shorten the discussion 1.Abstract, methods: 'coronary artery stenosis (CAS)', should be Carotid artery stenosis.Revised accordingly 2. Introduction : line 3: 'carotid artery stenosis', please add 'CAS'.Revised accordingly 3. Methods: 'this study was conducted based on the STROBE guideline'.Please add reference.We have added the reference 4. Results: "A total of 1314 patients with CAD were identified; 203 patients have [multi vascular disease]".Revised accordingly Competing Interests: No competing interests to disclose.The benefits of publishing with F1000Research: Your article is published within days, with no editorial bias • You can publish traditional articles, null/negative results, case reports, data notes and more • The peer review process is transparent and collaborative • Your article is indexed in PubMed after passing peer review • Dedicated customer support at every stage • For pre-submission enquiries, contact research@f1000.com

Table 2 .
24fference in prevalence of vascular disease between different severity of CAD.24

Table 3 .
24ctors significantly associated with multivascular disease in univariate analysis and stepwise logistic regression analysis.24

Table 5 .
24rformance of risk score in detecting vascular disease in CAD patients.24